From 2093b1ec059086e6c200519428fe1e0c0ba0cd5b Mon Sep 17 00:00:00 2001
From: tomrink <rink@ssec.wisc.edu>
Date: Tue, 5 Sep 2023 08:31:07 -0500
Subject: [PATCH] snapshot...
---
modules/deeplearning/cloud_opd_fcn_abi.py | 31 ++++++++++++++---------
1 file changed, 19 insertions(+), 12 deletions(-)
diff --git a/modules/deeplearning/cloud_opd_fcn_abi.py b/modules/deeplearning/cloud_opd_fcn_abi.py
index 3c57441b..02baf190 100644
--- a/modules/deeplearning/cloud_opd_fcn_abi.py
+++ b/modules/deeplearning/cloud_opd_fcn_abi.py
@@ -177,22 +177,29 @@ def get_min_max_std(grd_k):
def get_cldy_frac_opd(cld_prob, opd):
- cld_prob = np.where(np.isnan(cld_prob), 0, cld_prob)
+ cld_prob = np.where(np.isnan(cld_prob), 0.0, cld_prob)
+ opd = np.where(np.isnan(opd), 0.0, opd)
cld = np.where(cld_prob < 0.5, 0, 1)
- opd[cld == 0] = 0.0
- s = cld[:, 0::4, 0::4] + cld[:, 1::4, 0::4] + cld[:, 2::4, 0::4] + cld[:, 3::4, 0::4] + \
- cld[:, 0::4, 1::4] + cld[:, 1::4, 1::4] + cld[:, 2::4, 1::4] + cld[:, 3::4, 1::4] + \
- cld[:, 0::4, 2::4] + cld[:, 1::4, 2::4] + cld[:, 2::4, 2::4] + cld[:, 3::4, 2::4] + \
- cld[:, 0::4, 3::4] + cld[:, 1::4, 3::4] + cld[:, 2::4, 3::4] + cld[:, 3::4, 3::4]
+ cnt_cld = cld[:, 0::4, 0::4] + cld[:, 1::4, 0::4] + cld[:, 2::4, 0::4] + cld[:, 3::4, 0::4] + \
+ cld[:, 0::4, 1::4] + cld[:, 1::4, 1::4] + cld[:, 2::4, 1::4] + cld[:, 3::4, 1::4] + \
+ cld[:, 0::4, 2::4] + cld[:, 1::4, 2::4] + cld[:, 2::4, 2::4] + cld[:, 3::4, 2::4] + \
+ cld[:, 0::4, 3::4] + cld[:, 1::4, 3::4] + cld[:, 2::4, 3::4] + cld[:, 3::4, 3::4]
- cldy_opd = np.sum([opd[:, 0::4, 0::4], opd[:, 1::4, 0::4], opd[:, 2::4, 0::4], opd[:, 3::4, 0::4],
- opd[:, 0::4, 1::4], opd[:, 1::4, 1::4], opd[:, 2::4, 1::4], opd[:, 3::4, 1::4],
- opd[:, 0::4, 2::4], opd[:, 1::4, 2::4], opd[:, 2::4, 2::4], opd[:, 3::4, 2::4],
- opd[:, 0::4, 3::4], opd[:, 1::4, 3::4], opd[:, 2::4, 3::4], opd[:, 3::4, 3::4]], axis=0)
+ opd_sum = np.sum([opd[:, 0::4, 0::4], opd[:, 1::4, 0::4], opd[:, 2::4, 0::4], opd[:, 3::4, 0::4],
+ opd[:, 0::4, 1::4], opd[:, 1::4, 1::4], opd[:, 2::4, 1::4], opd[:, 3::4, 1::4],
+ opd[:, 0::4, 2::4], opd[:, 1::4, 2::4], opd[:, 2::4, 2::4], opd[:, 3::4, 2::4],
+ opd[:, 0::4, 3::4], opd[:, 1::4, 3::4], opd[:, 2::4, 3::4], opd[:, 3::4, 3::4]], axis=0)
- s = np.where(s == 0, 16, s)
- cldy_opd /= s
+ opd[cld == 0] = 0.0
+ cld_opd_sum = np.sum([opd[:, 0::4, 0::4], opd[:, 1::4, 0::4], opd[:, 2::4, 0::4], opd[:, 3::4, 0::4],
+ opd[:, 0::4, 1::4], opd[:, 1::4, 1::4], opd[:, 2::4, 1::4], opd[:, 3::4, 1::4],
+ opd[:, 0::4, 2::4], opd[:, 1::4, 2::4], opd[:, 2::4, 2::4], opd[:, 3::4, 2::4],
+ opd[:, 0::4, 3::4], opd[:, 1::4, 3::4], opd[:, 2::4, 3::4], opd[:, 3::4, 3::4]], axis=0)
+
+ cldy_opd = np.zeros(cnt_cld.shape, dtype=opd.dtype)
+ cldy_opd[cnt_cld == 0] = opd_sum[cnt_cld == 0] / 16
+ cldy_opd[cnt_cld != 0] = cld_opd_sum[cnt_cld != 0] / cnt_cld[cnt_cld != 0]
return cldy_opd
--
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